_a_t_a_c_

_e_n_c_o_d_e___a_t_a_c_

Pipeline version: v1

Report generated at 2019-06-24 04:12:53

Paired-end: [True, True, True]

Pipeline type: ATAC-Seq

Genome: GRCh38_no_alt_analysis_set_GCA_000001405.15.fasta.gz]

Peak caller: MACS2

Alignment


Flagstat (raw BAM)

rep1 (PE)rep2 (PE)rep3 (PE)
Total167967377211883832204502326
Total(QC-failed)000
Dupes000
Dupes(QC-failed)000
Mapped166911428210331491202793040
Mapped(QC-failed)000
% Mapped99.370099.270099.1600
Paired632108167813978876831552
Paired(QC-failed)000
Read1316054083906989438415776
Read1(QC-failed)000
Read2316054083906989438415776
Read2(QC-failed)000
Properly Paired587479667260055671163874
Properly Paired(QC-failed)000
% Properly Paired92.940092.910092.6200
With itself620323007647989675003762
With itself(QC-failed)000
Singletons122567107551118504
Singletons(QC-failed)000
% Singleton0.19000.14000.1500
Diff. Chroms423604995557048
Diff. Chroms (QC-failed)000

Marking duplicates (filtered BAM)

Filtered out (samtools view -F 1804):


rep1 (PE)rep2 (PE)rep3 (PE)
Unpaired Reads000
Paired Reads192275252362203723457982
Unmapped Reads000
Unpaired Dupes000
Paired Dupes120843941609144015384218
Paired Opt. Dupes000
% Dupes/1000.62850.68120.6558

Library complexity (filtered non-mito BAM)

rep1 (PE)rep2 (PE)rep3 (PE)
Total Reads (Pairs)627754166992607404997
Distinct Reads (Pairs)575321060331156675872
One Read (Pair)567234559291956476186
Two Reads (Pairs)7196294207186831
NRF = Distinct/Total0.91650.90060.9015
PBC1 = OnePair/Distinct0.98590.98280.9701
PBC2 = OnePair/TwoPair78.824262.937934.6633

Mitochondrial reads are filtered out.

NRF (non redundant fraction)
PBC1 (PCR Bottleneck coefficient 1)
PBC2 (PCR Bottleneck coefficient 2)
PBC1 is the primary measure. Provisionally


Flagstat (filtered/deduped BAM)

Filtered and duplicates removed

rep1 (PE)rep2 (PE)rep3 (PE)
Total142862621506119416147528
Total(QC-failed)000
Dupes000
Dupes(QC-failed)000
Mapped142862621506119416147528
Mapped(QC-failed)000
% Mapped100.0000100.0000100.0000
Paired142862621506119416147528
Paired(QC-failed)000
Read1714313175305978073764
Read1(QC-failed)000
Read2714313175305978073764
Read2(QC-failed)000
Properly Paired142862621506119416147528
Properly Paired(QC-failed)000
% Properly Paired100.0000100.0000100.0000
With itself142862621506119416147528
With itself(QC-failed)000
Singletons000
Singletons(QC-failed)000
% Singleton0.00000.00000.0000
Diff. Chroms000
Diff. Chroms (QC-failed)000

Peak calling


IDR (Irreproducible Discovery Rate) plots

rep1-rep2
rep1-rep2
rep1-rep3
rep1-rep3
rep2-rep3
rep2-rep3
rep1-pr
rep1-pr
rep2-pr
rep2-pr
rep3-pr
rep3-pr
ppr
ppr

Reproducibility QC and peak detection statistics

The number of peaks is capped at 300K for peak-caller MACS2


overlapIDR
Nt13403148038
N18292234490
N26851923321
N310668049577
Np16206676312
N optimal16206676312
N conservative13403148038
Optimal Setpprppr
Conservative Setrep1-rep3rep1-rep3
Rescue Ratio1.20921.5886
Self Consistency Ratio1.55692.1259
Reproducibilitypassborderline

Overlapping peaks


IDR (Irreproducible Discovery Rate) peaks


Enrichment


Fraction of reads in overlapping peaks

rep1-rep2rep1-rep3rep2-rep3rep1-prrep2-prrep3-prppr
Fraction of Reads in Peak0.18260.19230.18800.19650.12440.21170.2100


Fraction of reads in IDR peaks

rep1-rep2rep1-rep3rep2-rep3rep1-prrep2-prrep3-prppr
Fraction of Reads in Peak0.10330.12050.11390.12640.06910.14410.1527


ATAQC


Summary table

rep1rep2rep3
GenomeGRCh38_no_alt_analysis_set_GCA_000001405.15.fasta.gzGRCh38_no_alt_analysis_set_GCA_000001405.15.fasta.gzGRCh38_no_alt_analysis_set_GCA_000001405.15.fasta.gz
Paired/single-endedPaired-endedPaired-endedPaired-ended
Read length515151
Read count from sequencer632108167813978876831552
Read count successfully aligned621548677658744775122266
Read count after filtering for mapping quality400331464894952848673489
Read count after removing duplicate reads279487523285808833289271
Read count after removing mitochondrial reads (final read count)142862621506119416147528
Mapping quality > q30 (out of total)40033146, 0.63332746724948949528, 0.62643538270248673489, 0.633509121357
Duplicates (after filtering)12084394, 0.62849516091440, 0.68120515384218, 0.65582
Mitochondrial reads (out of total)46283404, 0.2772932000859621557, 0.28346471903256646352, 0.27933084883
Duplicates that are mitochondrial (out of all dups)23149826, 0.9578397559730881304, 0.95955688241729337840, 0.953504429019
Final reads (after all filters)14286262, 0.22600977022715061194, 0.19274679885216147528, 0.210167926843
NRF = Distinct/Total0.916475, OK0.900564, OK0.901536, OK
PBC1 = OnePair/Distinct0.985944, OK0.982775, OK0.970088, OK
PBC2 = OnePair/TwoPair78.824171, OK62.937945, OK34.663337, OK
Picard est library size119317411255914413269883
Fraction of reads in nfr0.349165754795, out of range [0.4, inf]0.29569181969, out of range [0.4, inf]0.347437718642, out of range [0.4, inf]
Nfr / mono-nuc reads0.950375316459, out of range [2.5, inf]0.695454567137, out of range [2.5, inf]0.901382186207, out of range [2.5, inf]
Presence of nfr peakOKOKOK
Presence of mono-nuc peakOKOKOK
Presence of di-nuc peakOKOKOK
Naive overlap peaks162066, OK162066, OK162066, OK
Idr peaks76312, OK76312, OK76312, OK
Naive peak stats: min size73.000073.000073.0000
Naive peak stats: 25 percentile228.0000228.0000228.0000
Naive peak stats: 50 percentile (median)386.0000386.0000386.0000
Naive peak stats: 75 percentile640.0000640.0000640.0000
Naive peak stats: max size2267.00002267.00002267.0000
Naive peak stats: mean470.9625470.9625470.9625
Idr peak stats: min size73.000073.000073.0000
Idr peak stats: 25 percentile426.0000426.0000426.0000
Idr peak stats: 50 percentile (median)621.0000621.0000621.0000
Idr peak stats: 75 percentile864.0000864.0000864.0000
Idr peak stats: max size2267.00002267.00002267.0000
Idr peak stats: mean665.8127665.8127665.8127

Replicate 1

Sample Information

Sample
Genome GRCh38_no_alt_analysis_set_GCA_000001405.15.fasta.gz
Paired/Single-ended Paired-ended
Read length 51

Summary

Read count from sequencer 63,210,816
Read count successfully aligned 62,154,867
Read count after filtering for mapping quality 40,033,146
Read count after removing duplicate reads 27,948,752
Read count after removing mitochondrial reads (final read count) 14,286,262
Note that all these read counts are determined using 'samtools view' - as such,
these are all reads found in the file, whether one end of a pair or a single
end read. In other words, if your file is paired end, then you should divide
these counts by two. Each step follows the previous step; for example, the
duplicate reads were removed after reads were removed for low mapping quality.
This bar chart also shows the filtering process and where the reads were lost
over the process. Note that each step is sequential - as such, there may
have been more mitochondrial reads which were already filtered because of
high duplication or low mapping quality. Note that all these read counts are
determined using 'samtools view' - as such, these are all reads found in
the file, whether one end of a pair or a single end read. In other words,
if your file is paired end, then you should divide these counts by two.

Alignment statistics

Bowtie alignment log

31605408 reads; of these:
  31605408 (100.00%) were paired; of these:
    2231425 (7.06%) aligned concordantly 0 times
    8744837 (27.67%) aligned concordantly exactly 1 time
    20629146 (65.27%) aligned concordantly >1 times
    ----
    2231425 pairs aligned concordantly 0 times; of these:
      661651 (29.65%) aligned discordantly 1 time
    ----
    1569774 pairs aligned 0 times concordantly or discordantly; of these:
      3139548 mates make up the pairs; of these:
        1055949 (33.63%) aligned 0 times
        108756 (3.46%) aligned exactly 1 time
        1974843 (62.90%) aligned >1 times
98.33% overall alignment rate

  

Samtools flagstat

167967377 + 0 in total (QC-passed reads + QC-failed reads)
104756561 + 0 secondary
0 + 0 supplementary
0 + 0 duplicates
166911428 + 0 mapped (99.37%:-nan%)
63210816 + 0 paired in sequencing
31605408 + 0 read1
31605408 + 0 read2
58747966 + 0 properly paired (92.94%:-nan%)
62032300 + 0 with itself and mate mapped
122567 + 0 singletons (0.19%:-nan%)
425130 + 0 with mate mapped to a different chr
42360 + 0 with mate mapped to a different chr (mapQ>=5)

  
Note that the flagstat command counts alignments, not reads. please 
use the read counts table to get accurate counts of reads at each
stage of the pipeline.

Filtering statistics

Mapping quality > q30 (out of total) 40,033,146 0.633
Duplicates (after filtering) 12,084,394 0.628
Mitochondrial reads (out of total) 46,283,404 0.277
Duplicates that are mitochondrial (out of all dups) 23,149,826 0.958
Final reads (after all filters) 14,286,262 0.226
Mapping quality refers to the quality of the read being aligned to that
particular location in the genome. A standard quality score is > 30.
Duplications are often due to PCR duplication rather than two unique reads
mapping to the same location. High duplication is an indication of poor
libraries. Mitochondrial reads are often high in chromatin accessibility
assays because the mitochondrial genome is very open. A high mitochondrial
fraction is an indication of poor libraries. Based on prior experience, a
final read fraction above 0.70 is a good library.
  

Library complexity statistics

ENCODE library complexity metrics

Metric Result
NRF 0.916475 - OK
PBC1 0.985944 - OK
PBC2 78.824171 - OK
The non-redundant fraction (NRF) is the fraction of non-redundant mapped reads
in a dataset; it is the ratio between the number of positions in the genome
that uniquely mapped reads map to and the total number of uniquely mappable
reads. The NRF should be > 0.8. The PBC1 is the ratio of genomic locations
with EXACTLY one read pair over the genomic locations with AT LEAST one read
pair. PBC1 is the primary measure, and the PBC1 should be close to 1.
Provisionally 0-0.5 is severe bottlenecking, 0.5-0.8 is moderate bottlenecking,
0.8-0.9 is mild bottlenecking, and 0.9-1.0 is no bottlenecking. The PBC2 is
the ratio of genomic locations with EXACTLY one read pair over the genomic
locations with EXACTLY two read pairs. The PBC2 should be significantly
greater than 1.

Picard EstimateLibraryComplexity

11,931,741

Yield prediction

Preseq performs a yield prediction by subsampling the reads, calculating the
number of distinct reads, and then extrapolating out to see where the
expected number of distinct reads no longer increases. The confidence interval
gives a gauge as to the validity of the yield predictions.

Fragment length statistics

Metric Result
Fraction of reads in NFR 0.349165754795 out of range [0.4, inf]
NFR / mono-nuc reads 0.950375316459 out of range [2.5, inf]
Presence of NFR peak OK
Presence of Mono-Nuc peak OK
Presence of Di-Nuc peak OK
Open chromatin assays show distinct fragment length enrichments, as the cut
sites are only in open chromatin and not in nucleosomes. As such, peaks
representing different n-nucleosomal (ex mono-nucleosomal, di-nucleosomal)
fragment lengths will arise. Good libraries will show these peaks in a
fragment length distribution and will show specific peak ratios.

Peak statistics

Metric Result
Naive overlap peaks 162066 - OK
IDR peaks 76312 - OK

Naive overlap peak file statistics

Min size 73.0
25 percentile 228.0
50 percentile (median) 386.0
75 percentile 640.0
Max size 2267.0
Mean 470.962521442

IDR peak file statistics

Min size 73.0
25 percentile 426.0
50 percentile (median) 621.0
75 percentile 864.0
Max size 2267.0
Mean 665.812703114
For a good ATAC-seq experiment in human, you expect to get 100k-200k peaks
for a specific cell type.

Sequence quality metrics

GC bias

Open chromatin assays are known to have significant GC bias. Please take this
into consideration as necessary.

Replicate 2

Sample Information

Sample
Genome GRCh38_no_alt_analysis_set_GCA_000001405.15.fasta.gz
Paired/Single-ended Paired-ended
Read length 51

Summary

Read count from sequencer 78,139,788
Read count successfully aligned 76,587,447
Read count after filtering for mapping quality 48,949,528
Read count after removing duplicate reads 32,858,088
Read count after removing mitochondrial reads (final read count) 15,061,194
Note that all these read counts are determined using 'samtools view' - as such,
these are all reads found in the file, whether one end of a pair or a single
end read. In other words, if your file is paired end, then you should divide
these counts by two. Each step follows the previous step; for example, the
duplicate reads were removed after reads were removed for low mapping quality.
This bar chart also shows the filtering process and where the reads were lost
over the process. Note that each step is sequential - as such, there may
have been more mitochondrial reads which were already filtered because of
high duplication or low mapping quality. Note that all these read counts are
determined using 'samtools view' - as such, these are all reads found in
the file, whether one end of a pair or a single end read. In other words,
if your file is paired end, then you should divide these counts by two.

Alignment statistics

Bowtie alignment log

39069894 reads; of these:
  39069894 (100.00%) were paired; of these:
    2769616 (7.09%) aligned concordantly 0 times
    9999602 (25.59%) aligned concordantly exactly 1 time
    26300676 (67.32%) aligned concordantly >1 times
    ----
    2769616 pairs aligned concordantly 0 times; of these:
      716720 (25.88%) aligned discordantly 1 time
    ----
    2052896 pairs aligned 0 times concordantly or discordantly; of these:
      4105792 mates make up the pairs; of these:
        1552341 (37.81%) aligned 0 times
        116305 (2.83%) aligned exactly 1 time
        2437146 (59.36%) aligned >1 times
98.01% overall alignment rate

  

Samtools flagstat

211883832 + 0 in total (QC-passed reads + QC-failed reads)
133744044 + 0 secondary
0 + 0 supplementary
0 + 0 duplicates
210331491 + 0 mapped (99.27%:-nan%)
78139788 + 0 paired in sequencing
39069894 + 0 read1
39069894 + 0 read2
72600556 + 0 properly paired (92.91%:-nan%)
76479896 + 0 with itself and mate mapped
107551 + 0 singletons (0.14%:-nan%)
529216 + 0 with mate mapped to a different chr
49955 + 0 with mate mapped to a different chr (mapQ>=5)

  
Note that the flagstat command counts alignments, not reads. please 
use the read counts table to get accurate counts of reads at each
stage of the pipeline.

Filtering statistics

Mapping quality > q30 (out of total) 48,949,528 0.626
Duplicates (after filtering) 16,091,440 0.681
Mitochondrial reads (out of total) 59,621,557 0.283
Duplicates that are mitochondrial (out of all dups) 30,881,304 0.960
Final reads (after all filters) 15,061,194 0.193
Mapping quality refers to the quality of the read being aligned to that
particular location in the genome. A standard quality score is > 30.
Duplications are often due to PCR duplication rather than two unique reads
mapping to the same location. High duplication is an indication of poor
libraries. Mitochondrial reads are often high in chromatin accessibility
assays because the mitochondrial genome is very open. A high mitochondrial
fraction is an indication of poor libraries. Based on prior experience, a
final read fraction above 0.70 is a good library.
  

Library complexity statistics

ENCODE library complexity metrics

Metric Result
NRF 0.900564 - OK
PBC1 0.982775 - OK
PBC2 62.937945 - OK
The non-redundant fraction (NRF) is the fraction of non-redundant mapped reads
in a dataset; it is the ratio between the number of positions in the genome
that uniquely mapped reads map to and the total number of uniquely mappable
reads. The NRF should be > 0.8. The PBC1 is the ratio of genomic locations
with EXACTLY one read pair over the genomic locations with AT LEAST one read
pair. PBC1 is the primary measure, and the PBC1 should be close to 1.
Provisionally 0-0.5 is severe bottlenecking, 0.5-0.8 is moderate bottlenecking,
0.8-0.9 is mild bottlenecking, and 0.9-1.0 is no bottlenecking. The PBC2 is
the ratio of genomic locations with EXACTLY one read pair over the genomic
locations with EXACTLY two read pairs. The PBC2 should be significantly
greater than 1.

Picard EstimateLibraryComplexity

12,559,144

Yield prediction

Preseq performs a yield prediction by subsampling the reads, calculating the
number of distinct reads, and then extrapolating out to see where the
expected number of distinct reads no longer increases. The confidence interval
gives a gauge as to the validity of the yield predictions.

Fragment length statistics

Metric Result
Fraction of reads in NFR 0.29569181969 out of range [0.4, inf]
NFR / mono-nuc reads 0.695454567137 out of range [2.5, inf]
Presence of NFR peak OK
Presence of Mono-Nuc peak OK
Presence of Di-Nuc peak OK
Open chromatin assays show distinct fragment length enrichments, as the cut
sites are only in open chromatin and not in nucleosomes. As such, peaks
representing different n-nucleosomal (ex mono-nucleosomal, di-nucleosomal)
fragment lengths will arise. Good libraries will show these peaks in a
fragment length distribution and will show specific peak ratios.

Peak statistics

Metric Result
Naive overlap peaks 162066 - OK
IDR peaks 76312 - OK

Naive overlap peak file statistics

Min size 73.0
25 percentile 228.0
50 percentile (median) 386.0
75 percentile 640.0
Max size 2267.0
Mean 470.962521442

IDR peak file statistics

Min size 73.0
25 percentile 426.0
50 percentile (median) 621.0
75 percentile 864.0
Max size 2267.0
Mean 665.812703114
For a good ATAC-seq experiment in human, you expect to get 100k-200k peaks
for a specific cell type.

Sequence quality metrics

GC bias

Open chromatin assays are known to have significant GC bias. Please take this
into consideration as necessary.

Replicate 3

Sample Information

Sample
Genome GRCh38_no_alt_analysis_set_GCA_000001405.15.fasta.gz
Paired/Single-ended Paired-ended
Read length 51

Summary

Read count from sequencer 76,831,552
Read count successfully aligned 75,122,266
Read count after filtering for mapping quality 48,673,489
Read count after removing duplicate reads 33,289,271
Read count after removing mitochondrial reads (final read count) 16,147,528
Note that all these read counts are determined using 'samtools view' - as such,
these are all reads found in the file, whether one end of a pair or a single
end read. In other words, if your file is paired end, then you should divide
these counts by two. Each step follows the previous step; for example, the
duplicate reads were removed after reads were removed for low mapping quality.
This bar chart also shows the filtering process and where the reads were lost
over the process. Note that each step is sequential - as such, there may
have been more mitochondrial reads which were already filtered because of
high duplication or low mapping quality. Note that all these read counts are
determined using 'samtools view' - as such, these are all reads found in
the file, whether one end of a pair or a single end read. In other words,
if your file is paired end, then you should divide these counts by two.

Alignment statistics

Bowtie alignment log

38415776 reads; of these:
  38415776 (100.00%) were paired; of these:
    2833839 (7.38%) aligned concordantly 0 times
    10478898 (27.28%) aligned concordantly exactly 1 time
    25103039 (65.35%) aligned concordantly >1 times
    ----
    2833839 pairs aligned concordantly 0 times; of these:
      739480 (26.09%) aligned discordantly 1 time
    ----
    2094359 pairs aligned 0 times concordantly or discordantly; of these:
      4188718 mates make up the pairs; of these:
        1709286 (40.81%) aligned 0 times
        126334 (3.02%) aligned exactly 1 time
        2353098 (56.18%) aligned >1 times
97.78% overall alignment rate

  

Samtools flagstat

204502326 + 0 in total (QC-passed reads + QC-failed reads)
127670774 + 0 secondary
0 + 0 supplementary
0 + 0 duplicates
202793040 + 0 mapped (99.16%:-nan%)
76831552 + 0 paired in sequencing
38415776 + 0 read1
38415776 + 0 read2
71163874 + 0 properly paired (92.62%:-nan%)
75003762 + 0 with itself and mate mapped
118504 + 0 singletons (0.15%:-nan%)
520554 + 0 with mate mapped to a different chr
57048 + 0 with mate mapped to a different chr (mapQ>=5)

  
Note that the flagstat command counts alignments, not reads. please 
use the read counts table to get accurate counts of reads at each
stage of the pipeline.

Filtering statistics

Mapping quality > q30 (out of total) 48,673,489 0.634
Duplicates (after filtering) 15,384,218 0.656
Mitochondrial reads (out of total) 56,646,352 0.279
Duplicates that are mitochondrial (out of all dups) 29,337,840 0.954
Final reads (after all filters) 16,147,528 0.210
Mapping quality refers to the quality of the read being aligned to that
particular location in the genome. A standard quality score is > 30.
Duplications are often due to PCR duplication rather than two unique reads
mapping to the same location. High duplication is an indication of poor
libraries. Mitochondrial reads are often high in chromatin accessibility
assays because the mitochondrial genome is very open. A high mitochondrial
fraction is an indication of poor libraries. Based on prior experience, a
final read fraction above 0.70 is a good library.
  

Library complexity statistics

ENCODE library complexity metrics

Metric Result
NRF 0.901536 - OK
PBC1 0.970088 - OK
PBC2 34.663337 - OK
The non-redundant fraction (NRF) is the fraction of non-redundant mapped reads
in a dataset; it is the ratio between the number of positions in the genome
that uniquely mapped reads map to and the total number of uniquely mappable
reads. The NRF should be > 0.8. The PBC1 is the ratio of genomic locations
with EXACTLY one read pair over the genomic locations with AT LEAST one read
pair. PBC1 is the primary measure, and the PBC1 should be close to 1.
Provisionally 0-0.5 is severe bottlenecking, 0.5-0.8 is moderate bottlenecking,
0.8-0.9 is mild bottlenecking, and 0.9-1.0 is no bottlenecking. The PBC2 is
the ratio of genomic locations with EXACTLY one read pair over the genomic
locations with EXACTLY two read pairs. The PBC2 should be significantly
greater than 1.

Picard EstimateLibraryComplexity

13,269,883

Yield prediction

Preseq performs a yield prediction by subsampling the reads, calculating the
number of distinct reads, and then extrapolating out to see where the
expected number of distinct reads no longer increases. The confidence interval
gives a gauge as to the validity of the yield predictions.

Fragment length statistics

Metric Result
Fraction of reads in NFR 0.347437718642 out of range [0.4, inf]
NFR / mono-nuc reads 0.901382186207 out of range [2.5, inf]
Presence of NFR peak OK
Presence of Mono-Nuc peak OK
Presence of Di-Nuc peak OK
Open chromatin assays show distinct fragment length enrichments, as the cut
sites are only in open chromatin and not in nucleosomes. As such, peaks
representing different n-nucleosomal (ex mono-nucleosomal, di-nucleosomal)
fragment lengths will arise. Good libraries will show these peaks in a
fragment length distribution and will show specific peak ratios.

Peak statistics

Metric Result
Naive overlap peaks 162066 - OK
IDR peaks 76312 - OK

Naive overlap peak file statistics

Min size 73.0
25 percentile 228.0
50 percentile (median) 386.0
75 percentile 640.0
Max size 2267.0
Mean 470.962521442

IDR peak file statistics

Min size 73.0
25 percentile 426.0
50 percentile (median) 621.0
75 percentile 864.0
Max size 2267.0
Mean 665.812703114
For a good ATAC-seq experiment in human, you expect to get 100k-200k peaks
for a specific cell type.

Sequence quality metrics

GC bias

Open chromatin assays are known to have significant GC bias. Please take this
into consideration as necessary.